4 Types of Healthcare Data Analysts Should Know

Summary

In this video, Josh Matlock, a clinical data analyst with eight years of experience, breaks down the four major types of healthcare data that professionals may encounter: EHR data, claims data, clinical and disease registries, and external reporting data. He explains how data is stored and accessed, using EHRs as an example of complex systems requiring processes like ETL to make data usable. Additionally, he discusses how claims data aids in fraud prevention, registries support quality improvement, and external reporting helps hospitals benchmark performance. This comprehensive guide offers insights into the role of data in healthcare analytics.

Takeaways

• 😀 EHR data (Electronic Health Records) includes a wide range of patient information, such as demographics, diagnoses, procedures, lab results, and more.
• 😀 EHR data is stored in a complex structure (like a tree) and often needs to be converted into a relational database format via ETL (Extract, Transform, Load) processes for analysis.
• 😀 Claims data consists of requests for reimbursement submitted by healthcare providers to insurance companies, including details such as procedure codes, diagnosis codes, and the amount paid out.
• 😀 While EHR data provides detailed clinical information, claims data offers a broader view but lacks specific details like test results.
• 😀 Claims data is useful for identifying fraud, analyzing cost drivers in healthcare, and evaluating the quality of care across multiple organizations.
• 😀 Clinical and disease registries collect data on specific diseases or surgeries, which are analyzed to improve care quality and identify trends across healthcare organizations.
• 😀 Disease registries, like the National Surgery Quality Improvement Program (NSQIP), help hospitals track surgical outcomes and compare performance to other institutions.
• 😀 External reporting data includes required and optional data that healthcare organizations must submit to regulatory bodies, such as adverse event reports or infection tracking to the CDC.
• 😀 Required external reporting includes submissions to state and federal governments, such as adverse events or hospital-acquired infections.
• 😀 Optional external reporting allows hospitals to share data for benchmarking purposes, which can improve their reputation, attract patients, and gain insights into care quality across similar organizations.
• 😀 Hospitals participate in various registries and reporting initiatives to improve care quality, obtain accreditation, and be compared to other institutions for performance improvements.

Q & A

What are the four major types of healthcare data mentioned in the video?

The four major types of healthcare data are EHR data, claims data, clinical and disease registries, and external reporting data.

What is an Electronic Health Record (EHR), and why is it important?

An Electronic Health Record (EHR) is a digital system that healthcare professionals use to document patient information, including medical history, diagnoses, treatments, and lab results. EHRs are important because they provide a comprehensive, centralized view of patient data, improving care coordination and efficiency.

Why is EHR data difficult to analyze directly from the system using SQL?

EHR data is often stored in a non-relational format (such as M's language), which organizes data in a tree-like structure, unlike relational databases that store data in tables. To analyze this data, it needs to be transformed into a tabular format through an ETL (Extract, Transform, Load) process.

How does claims data differ from EHR data in terms of detail?

Claims data generally contains less clinical detail than EHR data. While EHRs include detailed patient information like lab results and medical observations, claims data focuses on financial aspects, such as procedure codes, diagnosis codes, and reimbursement details.

What is the primary purpose of claims data in healthcare?

Claims data is used to track reimbursements and to evaluate healthcare costs. It is also important for detecting fraud, assessing cost drivers in healthcare, and analyzing the relationship between the quality of care and the amount paid by insurance providers.

What are clinical and disease registries, and how do they support healthcare organizations?

Clinical and disease registries are databases that focus on specific diseases or conditions, such as cancer or stroke. They collect patient data for research, quality improvement, and comparison across institutions. These registries help healthcare organizations improve care quality, track outcomes, and earn accreditations.

What role does a data abstractor play in maintaining disease registries?

A data abstractor collects relevant clinical data from patient records and enters it into disease-specific registries. This process requires understanding detailed medical records and may involve reviewing operative notes, lab results, and other clinical information.

How is external reporting data categorized in healthcare?

External reporting data is categorized into required reporting and optional reporting. Required reporting includes data that healthcare organizations must submit to government agencies, while optional reporting involves voluntarily sharing data with organizations for benchmarking and quality improvement.

Why might a hospital participate in optional reporting despite it not being legally required?

Hospitals may participate in optional reporting to gain access to benchmarking data, improve their reputation, attract patients, and attract skilled physicians. Participating in such programs can also help hospitals negotiate better deals with insurance companies.

What is the purpose of benchmarking in healthcare, and how does it benefit hospitals?

Benchmarking in healthcare allows hospitals to compare their performance with similar institutions. It helps identify strengths and weaknesses, informs quality improvement efforts, and can enhance a hospital's reputation, potentially leading to more patients and higher funding.